Showing papers by "City University of Hong Kong published in 2011"

Corporate Philanthropy and Corporate Financial Performance: The Roles of Stakeholder Response and Political Access

Abstract: Corporate philanthropy is expected to positively affect firm financial performance because it helps firms gain sociopolitical legitimacy, which enables them to elicit positive stakeholder responses...

Physical layer security in wireless networks: a tutorial

Abstract: Wireless networking plays an extremely important role in civil and military applications. However, security of information transfer via wireless networks remains a challenging issue. It is critical to ensure that confidential data are accessible only to the intended users rather than intruders. Jamming and eavesdropping are two primary attacks at the physical layer of a wireless network. This article offers a tutorial on several prevalent methods to enhance security at the physical layer in wireless networks. We classify these methods based on their characteristic features into five categories, each of which is discussed in terms of two metrics. First, we compare their secret channel capacities, and then we show their computational complexities in exhaustive key search. Finally, we illustrate their security requirements via some examples with respect to these two metrics.

In Vivo Pharmacokinetics, Long-Term Biodistribution, and Toxicology of PEGylated Graphene in Mice

Abstract: Graphene has emerged as interesting nanomaterials with promising applications in a range of fields including biomedicine. In this work, for the first time we study the long-term in vivo biodistribution of 125I-labeled nanographene sheets (NGS) functionalized with polyethylene glycol (PEG) and systematically examine the potential toxicity of graphene over time. Our results show that PEGylated NGS mainly accumulate in the reticuloendothelial system (RES) including liver and spleen after intravenous administration and can be gradually cleared, likely by both renal and fecal excretion. PEGylated NGS do not cause appreciable toxicity at our tested dose (20 mg/kg) to the treated mice in a period of 3 months as evidenced by blood biochemistry, hematological analysis, and histological examinations. Our work greatly encourages further studies of graphene for biomedical applications.

CFOs versus CEOs: Equity Incentives and Crashes

Abstract: Using a large sample of U.S. firms for the period 1993-2009, we provide evidence that the sensitivity of a chief financial officer’s (CFO) option portfolio value to stock price is significantly and positively related to the firm’s future stock price crash risk. In contrast, we find only weak evidence of the positive impact of chief executive officer option sensitivity on crash risk. Finally, we find that the link between CFO option sensitivity and crash risk is more pronounced for firms in non-competitive industries and those with a high level of financial leverage.

Silicon Nanowires for Photovoltaic Solar Energy Conversion

Abstract: Semiconductor nanowires are attracting intense interest as a promising material for solar energy conversion for the new-generation photovoltaic (PV) technology. In particular, silicon nanowires (SiNWs) are under active investigation for PV applications because they offer novel approaches for solar-to-electric energy conversion leading to high-efficiency devices via simple manufacturing. This article reviews the recent developments in the utilization of SiNWs for PV applications, the relationship between SiNW-based PV device structure and performance, and the challenges to obtaining high-performance cost-effective solar cells.

A new chaos-based fast image encryption algorithm

Abstract: In recent years, various image encryption algorithms based on the permutation-diffusion architecture have been proposed where, however, permutation and diffusion are considered as two separate stages, both requiring image-scanning to obtain pixel values. If these two stages are combined, the duplicated scanning effort can be reduced and the encryption can be accelerated. In this paper, a fast image encryption algorithm with combined permutation and diffusion is proposed. First, the image is partitioned into blocks of pixels. Then, spatiotemporal chaos is employed to shuffle the blocks and, at the same time, to change the pixel values. Meanwhile, an efficient method for generating pseudorandom numbers from spatiotemporal chaos is suggested, which further increases the encryption speed. Theoretical analyses and computer simulations both confirm that the new algorithm has high security and is very fast for practical image encryption.

Nanograssed Micropyramidal Architectures for Continuous Dropwise Condensation

Abstract: Engineering the dropwise condensation of water on surfaces is critical in a wide range of applications from thermal management (e.g. heat pipes, chip cooling etc.) to water harvesting technologies. Surfaces that enable both effi cient droplet nucleation and droplet self-removal (i.e. droplet departure) are essential to accomplish successful dropwise condensation. However it is extremely challenging to design such surfaces. This is because droplet nucleation requires a wettable surface while droplet departure necessitates a super-hydrophobic surface. Here we report that these confl icting requirements can be satisfi ed using a hierarchical (multiscale) nanograssed micropyramid architecture that yield a gobal superhydrophobicity as well as locally wettable nucleation sites, allowing for ˜65% increase in the drop number density and ˜450% increase in the drop self-removal volume as compared to a superhydrophobic surface with nanostructures alone. Further we fi that synergistic co-operation between the hierarchical structures contributes directly to a continuous process of nucleation, coalescence, departure, and re-nucleation enabling sustained dropwise condensation over prolonged periods. Exploiting such multiscale coupling effects can open up novel and exciting vistas in surface engineering leading to optimal condensation surfaces for high performance electronics cooling and water condenser systems.

Synchronous bursts on scale-free neuronal networks with attractive and repulsive coupling.

Abstract: This paper investigates the dependence of synchronization transitions of bursting oscillations on the information transmission delay over scale-free neuronal networks with attractive and repulsive coupling. It is shown that for both types of coupling, the delay always plays a subtle role in either promoting or impairing synchronization. In particular, depending on the inherent oscillation period of individual neurons, regions of irregular and regular propagating excitatory fronts appear intermittently as the delay increases. These delay-induced synchronization transitions are manifested as well-expressed minima in the measure for spatiotemporal synchrony. For attractive coupling, the minima appear at every integer multiple of the average oscillation period, while for the repulsive coupling, they appear at every odd multiple of the half of the average oscillation period. The obtained results are robust to the variations of the dynamics of individual neurons, the system size, and the neuronal firing type. Hence, they can be used to characterize attractively or repulsively coupled scale-free neuronal networks with delays.

A comparative assessment of ensemble learning for credit scoring

Abstract: Both statistical techniques and Artificial Intelligence (AI) techniques have been explored for credit scoring, an important finance activity. Although there are no consistent conclusions on which ones are better, recent studies suggest combining multiple classifiers, i.e., ensemble learning, may have a better performance. In this study, we conduct a comparative assessment of the performance of three popular ensemble methods, i.e., Bagging, Boosting, and Stacking, based on four base learners, i.e., Logistic Regression Analysis (LRA), Decision Tree (DT), Artificial Neural Network (ANN) and Support Vector Machine (SVM). Experimental results reveal that the three ensemble methods can substantially improve individual base learners. In particular, Bagging performs better than Boosting across all credit datasets. Stacking and Bagging DT in our experiments, get the best performance in terms of average accuracy, type I error and type II error.

Observer-Based Adaptive Fuzzy Backstepping Dynamic Surface Control for a Class of MIMO Nonlinear Systems

Abstract: In this paper, an adaptive fuzzy backstepping dynamic surface control (DSC) approach is developed for a class of multiple-input-multiple-output nonlinear systems with immeasurable states. Using fuzzy-logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed to estimate the immeasurable states. By combining adaptive-backstepping technique and DSC technique, an adaptive fuzzy output-feedback backstepping-control approach is developed. The proposed control method not only overcomes the problem of “explosion of complexity” inherent in the backstepping-design methods but also overcomes the problem of unavailable state measurements. It is proved that all the signals of the closed-loop adaptive-control system are semiglobally uniformly ultimately bounded, and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approach.

Active vision in robotic systems: A survey of recent developments

Abstract: In this paper we provide a broad survey of developments in active vision in robotic applications over the last 15 years. With increasing demand for robotic automation, research in this area has received much attention. Among the many factors that can be attributed to a high-performance robotic system, the planned sensing or acquisition of perceptions on the operating environment is a crucial component. The aim of sensor planning is to determine the pose and settings of vision sensors for undertaking a vision-based task that usually requires obtaining multiple views of the object to be manipulated. Planning for robot vision is a complex problem for an active system due to its sensing uncertainty and environmental uncertainty. This paper describes such problems arising from many applications, e.g. object recognition and modeling, site reconstruction and inspection, surveillance, tracking and search, as well as robotic manipulation and assembly, localization and mapping, navigation and exploration. A bundle of solutions and methods have been proposed to solve these problems in the past. They are summarized in this review while enabling readers to easily refer solution methods for practical applications. Representative contributions, their evaluations, analyses, and future research trends are also addressed in an abstract level.

Enhanced cell sorting and manipulation with combined optical tweezer and microfluidic chip technologies

Abstract: Sorting (or isolation) and manipulation of rare cells with high recovery rate and purity are of critical importance to a wide range of physiological applications. In the current paper, we report on a generic single cell manipulation tool that integrates optical tweezers and microfluidic chip technologies for handling small cell population sorting with high accuracy. The laminar flow nature of microfluidics enables the targeted cells to be focused on a desired area for cell isolation. To recognize the target cells, we develop an image processing methodology with a recognition capability of multiple features, e.g., cell size and fluorescence label. The target cells can be moved precisely by optical tweezers to the desired destination in a noninvasive manner. The unique advantages of this sorter are its high recovery rate and purity in small cell population sorting. The design is based on dynamic fluid and dynamic light pattern, in which single as well as multiple laser traps are employed for cell transportation, and a recognition capability of multiple cell features. Experiments of sorting yeast cells and human embryonic stem cells are performed to demonstrate the effectiveness of the proposed cell sorting approach.

Battery Management Systems in Electric and Hybrid Vehicles

Abstract: The battery management system (BMS) is a critical component of electric and hybrid electric vehicles. The purpose of the BMS is to guarantee safe and reliable battery operation. To maintain the safety and reliability of the battery, state monitoring and evaluation, charge control, and cell balancing are functionalities that have been implemented in BMS. As an electrochemical product, a battery acts differently under different operational and environmental conditions. The uncertainty of a battery’s performance poses a challenge to the implementation of these functions. This paper addresses concerns for current BMSs. State evaluation of a battery, including state of charge, state of health, and state of life, is a critical task for a BMS. Through reviewing the latest methodologies for the state evaluation of batteries, the future challenges for BMSs are presented and possible solutions are proposed as well.

Consensus in Directed Networks of Agents With Nonlinear Dynamics

Abstract: This technical note studies the consensus problem for cooperative agents with nonlinear dynamics in a directed network. Both local and global consensus are defined and investigated. Techniques for studying the synchronization in such complex networks are exploited to establish various sufficient conditions for reaching consensus. The local consensus problem is first studied via a combination of the tools of complex analysis, local consensus manifold approach, and Lyapunov methods. A generalized algebraic connectivity is then proposed to study the global consensus problem in strongly connected networks and also in a broad class of networks containing spanning trees, for which ideas from algebraic graph theory, matrix theory, and Lyapunov methods are utilized.